DocumentCode :
1641124
Title :
Risk minimization with self-organizing maps for mutual fund investment
Author :
Lukyanitsa, Andrei A. ; Nosov, Sergei V. ; Shishkin, Alexei G.
Author_Institution :
Dept. of Comput. Math.&Cybern., Moscow State Univ., Moscow
fYear :
2009
Firstpage :
2361
Lastpage :
2365
Abstract :
The problem of optimal mutual fund investment taking into account possible risks is considered. In this paper we consider lost profit in the growing market and a loss in a falling market as a possible risk. Our studies show that the efficiency of mutual funds can be estimated by nine main parameters obtained by historical data. Evaluation and ranking criteria sets for mutual funds are defined by the help of Kohonen Self-Organizing Maps. We propose to use a simplified ranking consisting of five categories. The methodology of constructing optimal strategies for risk-sensitive portfolio optimization is proposed. The performance of constructed portfolio is superior to the most mutual funds and other portfolios. The proposed methodology underwent a test for last four years and showed high efficiency and robustness both in growing and falling (during current world financial crisis) markets.
Keywords :
genetic algorithms; investment; probability; profitability; risk management; self-organising feature maps; genetic algorithm; mutual fund investment; probability; profitability; risk minimization; risk-sensitive portfolio optimization; self-organizing Kohonen map; Cybernetics; Instruments; Investments; Mathematics; Mutual funds; Optimization methods; Portfolios; Risk management; Robustness; Self organizing feature maps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
Type :
conf
DOI :
10.1109/CEC.2009.4983235
Filename :
4983235
Link To Document :
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